Research
Our approach to quantitative research emphasizes rigor, reproducibility, and continuous validation.
Data & Labeling
We maintain comprehensive datasets across on-chain and off-chain sources. All data undergoes rigorous validation, cleaning, and labeling processes. We document data provenance, quality metrics, and potential biases to ensure research integrity.
Backtesting and Leakage Controls
Our backtesting framework enforces strict temporal ordering and prevents look-ahead bias. We implement walk-forward analysis, out-of-sample testing, and adversarial scenario generation. All models are validated against multiple market regimes and stress conditions.
Validation Across Regimes
We test strategies across different market conditions, volatility regimes, and structural changes. This includes bull markets, bear markets, high volatility periods, and regime shifts. Models must demonstrate robustness before deployment.
Deployment and Monitoring
Production systems include real-time monitoring, alerting, and automated risk controls. We track performance metrics, model drift, and operational health continuously. All systems are designed with fail-safes and circuit breakers.
Research Process
Data Collection
Aggregate and validate
Hypothesis Formation
Define testable questions
Backtesting
Rigorous validation
Deployment
Production monitoring
Research Notes
Market microstructure in decentralized exchanges
Cross-chain arbitrage opportunities and execution
On-chain data aggregation and signal extraction
Risk-adjusted portfolio construction for digital assets
Latency optimization in high-frequency trading systems